# A framework for cross-validated classification problems, with applications to differential variability and differential distribution testing

## Documentation for package ‘ClassifyR’ version 2.14.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E F G I K L M N P R S T misc

## -- A --

actualClasses | Container for Storing Classification Results
actualClasses-method | Container for Storing Classification Results

## -- B --

bartlettSelection | Selection of Differential Variability with Bartlett Statistic
bartlettSelection-method | Selection of Differential Variability with Bartlett Statistic

## -- C --

calcCVperformance | Add Performance Calculations to a ClassifyResult Object or Calculate for a Pair of Factor Vectors
calcCVperformance-method | Add Performance Calculations to a ClassifyResult Object or Calculate for a Pair of Factor Vectors
calcExternalPerformance | Add Performance Calculations to a ClassifyResult Object or Calculate for a Pair of Factor Vectors
calcExternalPerformance-method | Add Performance Calculations to a ClassifyResult Object or Calculate for a Pair of Factor Vectors
calcPerformance | Add Performance Calculations to a ClassifyResult Object or Calculate for a Pair of Factor Vectors
characterOrDataFrame | Union of a Character and a DataFrame
characterOrDataFrame-class | Union of a Character and a DataFrame
classes | Asthma RNA Abundance and Patient Classes
classifyInterface | An Interface for PoiClaClu Package's Classify Function
classifyInterface-method | An Interface for PoiClaClu Package's Classify Function
ClassifyResult | Container for Storing Classification Results
ClassifyResult-class | Container for Storing Classification Results
ClassifyResult-method | Container for Storing Classification Results

## -- D --

differentMeansSelection | Selection of Differentially Abundant Features
differentMeansSelection-method | Selection of Differentially Abundant Features
distribution | Get Frequencies of Feature Selection and Sample Errors
distribution-method | Get Frequencies of Feature Selection and Sample Errors
dlda | Trained dlda Object
dlda-class | Trained dlda Object
DLDApredictInterface | An Interface for sparsediscrim Package's dlda Function
DLDApredictInterface-method | An Interface for sparsediscrim Package's dlda Function
DLDAtrainInterface | An Interface for sparsediscrim Package's dlda Function
DLDAtrainInterface-method | An Interface for sparsediscrim Package's dlda Function
DMDselection | Selection of Differential Distributions with Differences in Means or Medians and a Deviation Measure
DMDselection-method | Selection of Differential Distributions with Differences in Means or Medians and a Deviation Measure

## -- E --

EasyHardClassifier | Container for a Pair of Trained Classifiers
easyHardClassifier | Two-stage Classification Using Easy-to-collect Data Set and Hard-to-collect data set.
EasyHardClassifier-class | Container for a Pair of Trained Classifiers
EasyHardClassifier-method | Container for a Pair of Trained Classifiers
easyHardClassifierPredict | Two-stage Classification Using Easy-to-collect Data Set and Hard-to-collect data set.
easyHardClassifierPredict-method | Two-stage Classification Using Easy-to-collect Data Set and Hard-to-collect data set.
easyHardClassifierTrain | Two-stage Classification Using Easy-to-collect Data Set and Hard-to-collect data set.
easyHardClassifierTrain-method | Two-stage Classification Using Easy-to-collect Data Set and Hard-to-collect data set.
easyHardFeatures | Extract Chosen Features from an EasyHardClassifier Object
easyHardFeatures-method | Extract Chosen Features from an EasyHardClassifier Object
edgeRselection | Feature Selection Based on Differential Expression for Count Data
edgeRselection-method | Feature Selection Based on Differential Expression for Count Data
edgesToHubNetworks | Convert a Two-column Matrix or Data Frame into a Hub Node List
elasticNetFeatures | Extract Vectors of Ranked and Selected Features From an Elastic Net GLM Object
elasticNetFeatures-method | Extract Vectors of Ranked and Selected Features From an Elastic Net GLM Object
elasticNetGLMinterface | An Interface for glmnet Package's glmnet Function
elasticNetGLMpredictInterface | An Interface for glmnet Package's glmnet Function
elasticNetGLMpredictInterface-method | An Interface for glmnet Package's glmnet Function
elasticNetGLMtrainInterface | An Interface for glmnet Package's glmnet Function
elasticNetGLMtrainInterface-method | An Interface for glmnet Package's glmnet Function

## -- F --

featureNames | Container for Storing Classification Results
featureNames-method | Container for Storing Classification Results
features | Container for Storing Classification Results
features-method | Container for Storing Classification Results
FeatureSetCollection | Container for Storing A Collection of Sets
FeatureSetCollection-class | Container for Storing A Collection of Sets
FeatureSetCollection-method | Container for Storing A Collection of Sets
FeatureSetCollectionOrNULL | Union of a FeatureSetCollection and NULL
FeatureSetCollectionOrNULL-class | Union of a FeatureSetCollection and NULL
featureSetSummary | Transform a Table of Feature Abundances into a Table of Feature Set Abundances.
featureSetSummary-method | Transform a Table of Feature Abundances into a Table of Feature Set Abundances.
fisherDiscriminant | Classification Using Fisher's LDA
fisherDiscriminant-method | Classification Using Fisher's LDA
forestFeatures | Extract Vectors of Ranked and Selected Features From a Random Forest Object
forestFeatures-method | Extract Vectors of Ranked and Selected Features From a Random Forest Object
functionOrList | Union of Functions and List of Functions
functionOrList-class | Union of Functions and List of Functions
functionOrNULL | Union of A Function and NULL
functionOrNULL-class | Union of A Function and NULL

## -- G --

getLocationsAndScales | Calculate Location and Scale
getLocationsAndScales-method | Calculate Location and Scale

## -- I --

integerOrNumeric | Union of a Integer and a Numeric
integerOrNumeric-class | Union of a Integer and a Numeric
interactorDifferences | Convert Individual Features into Differences Between Binary Interactors Based on Known Sub-networks
interactorDifferences-method | Convert Individual Features into Differences Between Binary Interactors Based on Known Sub-networks

## -- K --

kNNinterface | An Interface for class Package's knn Function
kNNinterface-method | An Interface for class Package's knn Function
KolmogorovSmirnovSelection | Selection of Differential Distributions with Kolmogorov-Smirnov Distance
KolmogorovSmirnovSelection-method | Selection of Differential Distributions with Kolmogorov-Smirnov Distance
kTSPclassifier | Classification Using k Pairs of Features With Relative Differences Between Classes
kTSPclassifier-method | Classification Using k Pairs of Features With Relative Differences Between Classes
KullbackLeiblerSelection | Selection of Differential Distributions with Kullback-Leibler Distance
KullbackLeiblerSelection-method | Selection of Differential Distributions with Kullback-Leibler Distance

## -- L --

length-method | Container for Storing A Collection of Sets
leveneSelection | Selection of Differential Variability with Levene Statistic
leveneSelection-method | Selection of Differential Variability with Levene Statistic
likelihoodRatioSelection | Selection of Differential Distributions with Likelihood Ratio Statistic
likelihoodRatioSelection-method | Selection of Differential Distributions with Likelihood Ratio Statistic
limmaSelection | Selection of Differentially Abundant Features
limmaSelection-method | Selection of Differentially Abundant Features
listOrCharacterOrNULL | Union of a List and a Character Vector and NULL
listOrCharacterOrNULL-class | Union of a List and a Character Vector and NULL
listOrNULL | Union of a List and NULL
listOrNULL-class | Union of a List and NULL

## -- M --

measurements | Asthma RNA Abundance and Patient Classes
mixmodels | Classification based on Differential Distribution utilising Mixtures of Normals
MixModelsListsSet | Container for a List of Lists Containing Mixture Models
MixModelsListsSet-class | Container for a List of Lists Containing Mixture Models
MixModelsListsSet-method | Container for a List of Lists Containing Mixture Models
mixModelsPredict | Classification based on Differential Distribution utilising Mixtures of Normals
mixModelsPredict-method | Classification based on Differential Distribution utilising Mixtures of Normals
mixModelsTrain | Classification based on Differential Distribution utilising Mixtures of Normals
mixModelsTrain-method | Classification based on Differential Distribution utilising Mixtures of Normals
models | Container for Storing Classification Results
models-method | Container for Storing Classification Results
multnet | Trained multnet Object
multnet-class | Trained multnet Object

## -- N --

naiveBayesKernel | Classification Using A Bayes Classifier with Kernel Density Estimates
naiveBayesKernel-method | Classification Using A Bayes Classifier with Kernel Density Estimates
networkCorrelationsSelection | Selection of Differentially Correlated Hub Sub-networks
networkCorrelationsSelection-method | Selection of Differentially Correlated Hub Sub-networks
NSCpredictInterface | Interface for 'pamr.predict' Function from 'pamr' CRAN Package
NSCpredictInterface-method | Interface for 'pamr.predict' Function from 'pamr' CRAN Package
NSCselectionInterface | Interface for 'pamr.listgenes' Function from 'pamr' CRAN Package
NSCselectionInterface-method | Interface for 'pamr.listgenes' Function from 'pamr' CRAN Package
NSCtrainInterface | Interface for 'pamr.train' Function from 'pamr' CRAN Package
NSCtrainInterface-method | Interface for 'pamr.train' Function from 'pamr' CRAN Package

## -- P --

pairsDifferencesSelection | Selection of Pairs of Features that are Different Between Classes
pairsDifferencesSelection-method | Selection of Pairs of Features that are Different Between Classes
pamrtrained | Trained pamr Object
pamrtrained-class | Trained pamr Object
performance | Container for Storing Classification Results
performance-method | Container for Storing Classification Results
performancePlot | Plot Performance Measures for Various Classifications
performancePlot-method | Plot Performance Measures for Various Classifications
plotFeatureClasses | Plot Density, Scatterplot, Parallel Plot or Bar Chart for Features By Class
plotFeatureClasses-method | Plot Density, Scatterplot, Parallel Plot or Bar Chart for Features By Class
predictions | Container for Storing Classification Results
predictions-method | Container for Storing Classification Results
PredictParams | Parameters for Classifier Prediction
PredictParams-class | Parameters for Classifier Prediction
PredictParams-method | Parameters for Classifier Prediction
previousSelection | Automated Selection of Previously Selected Features
previousSelection-method | Automated Selection of Previously Selected Features
previousTrained | Automated Usage of Previously Created Classifiers
previousTrained-method | Automated Usage of Previously Created Classifiers

## -- R --

randomForest | Trained randomForest Object
randomForest-class | Trained randomForest Object
randomForestInterface | An Interface for randomForest Package's randomForest Function
randomForestPredictInterface | An Interface for randomForest Package's randomForest Function
randomForestPredictInterface-method | An Interface for randomForest Package's randomForest Function
randomForestTrainInterface | An Interface for randomForest Package's randomForest Function
randomForestTrainInterface-method | An Interface for randomForest Package's randomForest Function
rankingPlot | Plot Pair-wise Overlap of Ranked Features
rankingPlot-method | Plot Pair-wise Overlap of Ranked Features
ResubstituteParams | Parameters for Resubstitution Error Calculation
ResubstituteParams-class | Parameters for Resubstitution Error Calculation
ResubstituteParams-method | Parameters for Resubstitution Error Calculation
ROCplot | Plot Receiver Operating Curve Graphs for Classification Results
ROCplot-method | Plot Receiver Operating Curve Graphs for Classification Results
runTest | Perform a Single Classification
runTest-method | Perform a Single Classification
runTestEasyHard | Perform a Single Classification
runTestEasyHard-method | Perform a Single Classification
runTests | Reproducibly Run Various Kinds of Cross-Validation
runTests-method | Reproducibly Run Various Kinds of Cross-Validation
runTestsEasyHard | Reproducibly Run Various Kinds of Cross-Validation
runTestsEasyHard-method | Reproducibly Run Various Kinds of Cross-Validation

## -- S --

sampleNames | Container for Storing Classification Results
sampleNames-method | Container for Storing Classification Results
samplesMetricMap | Plot a Grid of Sample Error Rates or Accuracies
samplesMetricMap-method | Plot a Grid of Sample Error Rates or Accuracies
selectionPlot | Plot Pair-wise Overlap or Selection Size Distribution of Selected Features
selectionPlot-method | Plot Pair-wise Overlap or Selection Size Distribution of Selected Features
SelectParams | Parameters for Feature Selection
SelectParams-class | Parameters for Feature Selection
SelectParams-method | Parameters for Feature Selection
SelectResult | Container for Storing Feature Selection Results
SelectResult-class | Container for Storing Feature Selection Results
SelectResult-method | Container for Storing Feature Selection Results
show-method | Container for Storing Classification Results
show-method | Container for a Pair of Trained Classifiers
show-method | Container for Storing A Collection of Sets
show-method | Container for Storing Feature Selection Results
subtractFromLocation | Subtract Numeric Feature Measurements from a Location
subtractFromLocation-method | Subtract Numeric Feature Measurements from a Location
svm | Trained svm Object
svm-class | Trained svm Object
SVMpredictInterface | An Interface for e1071 Package's Support Vector Machine Classifier.
SVMpredictInterface-method | An Interface for e1071 Package's Support Vector Machine Classifier.
SVMtrainInterface | An Interface for e1071 Package's Support Vector Machine Classifier.
SVMtrainInterface-method | An Interface for e1071 Package's Support Vector Machine Classifier.

## -- T --

totalPredictions | Container for Storing Classification Results
totalPredictions-method | Container for Storing Classification Results
TrainParams | Parameters for Classifier Training
TrainParams-class | Parameters for Classifier Training
TrainParams-method | Parameters for Classifier Training
TransformParams | Parameters for Data Transformation
TransformParams-class | Parameters for Data Transformation
TransformParams-method | Parameters for Data Transformation
tunedParameters | Container for Storing Classification Results
tunedParameters-method | Container for Storing Classification Results

## -- misc --

[-method | Container for Storing A Collection of Sets
[[-method | Container for Storing A Collection of Sets